{ "background": "District hospitals are critical nodes in healthcare delivery, yet systematic evaluations of their system-level performance and its impact on clinical outcomes in sub-Saharan Africa are methodologically limited. Existing assessments often rely on aggregate data, failing to account for the hierarchical structure of patient care within hospital systems.", "purpose and objectives": "This study aims to methodologically evaluate the performance of district hospital systems in Kenya by developing and applying a multilevel regression framework to analyse variations in clinical outcomes attributable to hospital-level system factors.", "methodology": "We conducted a retrospective cohort analysis using anonymised patient records from a nationally representative sample of district hospitals. A three-level hierarchical logistic regression model was specified: $\\text{logit}(p{ijk}) = \\beta0 + \\beta X{ijk} + u{jk} + vk$, where $p{ijk}$ is the probability of a positive outcome for patient $i$ in department $j$ in hospital $k$, $X$ represents patient-level covariates, and $u{jk}$ and $vk$ are random intercepts for department and hospital, respectively. Model inference was based on 95% confidence intervals derived from robust standard errors.", "findings": "Hospital-level system factors, notably pharmacy stock-out rates and specialist clinician density, explained 22% (95% CI: 18 to 26) of the variance in risk-adjusted inpatient mortality. A one-standard-deviation increase in specialist density was associated with a 15% reduction in the odds of mortality.", "conclusion": "The methodological approach demonstrates that a significant proportion of variance in clinical outcomes is attributable to modifiable hospital system characteristics, moving beyond patient-level explanations.", "recommendations": "Hospital performance evaluations should adopt multilevel modelling to isolate system-level effects. Policy should prioritise investments in human resources and supply chain reliability to improve clinical outcomes.", "key words": "health systems evaluation, multilevel modelling, clinical outcomes, district hospitals, sub-Saharan Africa", "contribution statement":